Optical coherence tomography angiography measured capillary density in normal and glaucoma eyes

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Original Article

4

Optical coherence tomography angiography measured capillary

5

density in normal and glaucoma eyes

6 7

8

RPCs and ONH capillary density in glaucoma

9 Tarannum Mansoori^a,^⇑; Jahnavi Gamalapati^b; Jayanthi Sivaswamy^b; Nagalla Balakrishna^c

10

11 Abstract

12 Purpose: To compare the diagnostic ability of optical coherence tomography angiography (OCT-A) derived radial peripapillary

13 capillary (RPC) measured capillary density (CD) and inside the optic nerve head (ONH) CD measurements to differentiate between

14 the normal and primary open angle glaucoma (POAG) eyes.

15 Methods: AngioVue disc OCT-A images were obtained and assessed in 83 eyes of POAG patients and 74 age matched healthy

16 eyes. RPC CD was quantitatively measured in the peripapillary area within 3.45 mm circle diameter around the ONH and inside the

17 ONH in 8 equally divided sectors, using Bar – Selective Combination of Shifted Filter Responses method after the suppressing

18 large vessels. Area under receiver operating characteristic (AUROC) curve was used to assess the diagnostic accuracy of the

19 two scanning regions of CD to differentiate between the normal and POAG eyes.

20 Results: The mean peripapillary RPC density (0.12 ± 0.03) and mean ONH CD (0.09 ± 0.03) were significantly lower in POAG eyes

21 when compared to the normal eyes (RPC CD: 0.17 ± 0.05, p < 0.0001 and ONH CD 0.11 ± 0.02, p = 0.01 respectively). The POAG

22 patients showed 29% reduction in the RPC CD and 19% reduction in the ONH CD when compared to the normal eyes. The

23 AUROC for discriminating between healthy and glaucomatous eyes was 0.784 for mean RPC CD and 0.743 for the mean ONH CD.

24 Conclusions: Diagnostic ability of OCT-A derived peripapillary CD and ONH CD was moderate for differentiating between the

25 normal and glaucomatous eyes. Diagnostic ability of even the best peripapillary average and inferotemporal sector for RPC CD

26 and average and superonasal sector for the ONH CD was moderate.

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28 Keywords: POAG, Peripapillary capillary density, OCT-A, ONH capillary density

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30 Ó 2018 Production and hosting by Elsevier B.V. on behalf of Saudi Ophthalmological Society, King Saud University. This is an open

31 access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

32 https://doi.org/10.1016/j.sjopt.2018.09.006

33

34 Introduction

35 Glaucoma is a multi – factorial, progressive, optic neu-

36 ropathy with complex pathophysiology, which is character-

37 ized by the retinal ganglion cell axonal degeneration. The

38 role of optic nerve head (ONH) microvascular network in ocu-

lar blood flow and vascular dysfunction has been investigated 39

in the pathogenesis of glaucoma.¹ 40

Radial peripapillary capillaries (RPC) are a unique plexus of 41

capillary network, which display a characteristic linear mor- 42

phological pattern with a minimal inter capillary anastomosis. 43

They are restricted to the posterior pole and confined to the 44

Peer review under responsibility of Saudi Ophthalmological Society,

King Saud University Production and hosting by Elsevier

Access this article online:

www.saudiophthaljournal.com www.sciencedirect.com Received 4 April 2017; received in revised form 30 August 2018; accepted 25 September 2018; available online xxxx.

aAnand Eye Institute, Hyderabad, India

bInternational Institute of Information Technology, Hyderabad, India

cNational Institute of Nutrition, Hyderabad, India

⇑ Corresponding author at: Sita Lakshmi Glaucoma Center, Anand Eye Institute, 7-147/1, Nagendra Nagar, Habsiguda, Hyderabad 500007, India.

e-mail address:tarannummansoori@yahoo.com(T. Mansoori).

Please cite this article in press as: Mansoori T., et al. Optical coherence tomography angiography measured capillary density in normal and glaucoma eyes.

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45 inner aspect of the retinal nerve fiber layer (RNFL) around the

46 ONH.²Histological studies^3,4and imaging studies with Opti-

47 cal coherence tomography angiography (OCT-A)^5–11 have

48 highlighted the role of RPC and superficial retinal network

49 in the pathogenesis of glaucoma.

50 OCT-A with split spectrum amplitude-decorrelation

51 angiography (SSADA) algorithm is a new imaging modality

52 that can be used to visualize retinal and ONH vasculature in

53 the various retinal layers¹² and provides quantitative mea-

54 surement of the microcirculation in the peripapillary

55 region^7,9,10and ONH^6,10,11vessel density.

56 Bar –Selective Combination of Shifted Filter Responses (B-

57 COSFIRE) filter method is very effective in the detection and

58 quantitative estimation of the capillaries.¹³ A study by our

59 group has evaluated topological and quantitative measure-

60 ment of the OCT-A derived RPC network in the normal

61 healthy eyes with good intra-visit intra-operator repeatability

62 using B-COSFIRE method.¹⁴

63 The purpose of the current study was to compare the

64 diagnostic ability of OCT-A derived peripapillary RPC capil-

65 lary density (CD) and inside ONH CD for differentiating

66 healthy eyes and primary open angle glaucoma (POAG) eyes.

67 Material and methods

68 For this prospective study, healthy subjects and POAG

69 patients were enrolled after obtaining the informed consent.

70 The study was performed in accord with the tenets of the

71 Declaration of Helsinki for the research involving human

72 subjects.

73 All the participants underwent comprehensive ophthalmic

74 examination, including medical history, assessment of best-

75 corrected visual acuity, slit-lamp biomicroscopy examination,

76 intraocular pressure (IOP) measurement with Goldmann

77 applanation tonometry, gonioscopy with Sussman goniolens,

78 central corneal thickness (CCT) pachymetry measurement

79 with AL scan (Nidek CO, Ltd, Gamagori, Japan), dilated fun-

80 dus examination and perimetry with Swedish interactive

81 thresholding algorithm (SITA) standard 24-2 program using

82 Humphrey field analyzer (HFA 720 II Carl Zeiss Meditec,

83 Dublin, California, USA). OCT-A and spectral domain (SD)

84 OCT images were obtained by two experienced operators

85 on the same visit using the dual modality RTVue XR-100

86 OCT (Avanti, Optovue Inc., Fremont, CA, version

87 2015.1.0.90).

88 Healthy subjects had no history of elevated IOP, no family

89 history of glaucoma, IOP < 21 mm Hg, normal anterior and

90 posterior segment on clinical examination, normal optic disc

91 with intact neuroretinal rim and RNFL, reliable and normal

92 visual fields (defined as a Pattern standard deviation (PSD)

93 within 95% confidence limits and Glaucoma Hemifield Test

94 result within normal limits). Visual fields were considered reli-

95 able if the fixation losses were 20% and false-negative

96 errors and false-positive errors were15%, with no lens rim

97 or eyelid artifacts.

98 POAG patients had IOP > 21 mmHg, open angles on

99 gonioscopy, glaucomatous optic disc changes (Neuroretinal

100 rim thinning, rim notching or RNFL defect) reliable and

101 repeatable glaucomatous visual field defect defined as GHT

102 outside normal limits and PSD outside 95% normal confi-

103 dence limits.

Participants with a history of ocular trauma, intraocular 104

surgery, co existing corneal or retinal pathology, neurological 105

disease, non glaucomatous optic neuropathy, refractive 106

error ±6 Diopter (D) sphere and cylinder ±3D, media 107

opacities, unreliable visual field, poor quality OCT-A or 108

ONH SD-OCT images, were excluded from the study. 109

Optical coherence tomography angiography 110

Image acquisition and processing 111

The AngioVue Avanti OCT is a noninvasive OCT-based 112

method for visualizing the ONH and retinal vasculature. It 113

uses a 840-nm wavelength light source and a bandwidth of 114

50 nm. It has an A-scan rate of 70,000 scans per seconds, 115

axial resolution of 5µm in tissue and a 22 µm focal spot diam- 116

eter. Each volume contains 304 304 A-scans with two con- 117

secutive B-scans captured at a each fixed position. Each 118

image set comprises of a set of 2 scans: one vertical priority 119

(y-fast) and one horizontal priority (x-fast) raster volumetric 120

pattern. Each scan is acquired in less than 3 seconds. which 121

minimizes the motion artifacts. An orthogonal registration 122

algorithm is used to produce a 3 – dimensional OCT angio- 123

grams of the retinal vasculature by merging the 2 scans.¹⁵ 124

The SSADA method is used to compare the consecutive B 125

scans at the same location to capture the dynamic motion 126

of the red blood cells using motion contrast.¹² An enface 127

angiogram of the RPC segment was obtained by the maxi- 128

mum flow (decorrelation value) projection which extends 129

from the internal limiting membrane (ILM) to the posterior 130

boundary of RNFL covering, 4.5 mm 4.5 mm field of view 131

and centered on ONH. An enface angiogram of the ONH 132

segment was obtained in 4.5 4.5 mm field of view. 133

A trained examiner reviewed all the OCT-A scans and only 134

the images with good clarity, a signal strength index (SSI) of 135

more than 40, with no residual motion artifacts (irregular ves- 136

sel pattern on the enface angiogram) were included for the 137

analysis. 138

All the subjects also underwent ONH imaging with RTVue 139

– XR-100 SD-OCT system with the ONH map protocol to 140

obtain ONH structural measurements and peripapillary RNFL 141

thickness measurements along a circle diameter of 3.45 mm 142

centered on the ONH. The ONH scan is a combination of cir- 143

cular scans for RNFL thickness analysis and radial scans for 144

ONH shape analysis, which ensures that the RNFL and 145

ONH scan share the same center. Thirteen circle lines, with 146

the diameters of 1.3–4.9 mm are scanned and used to create 147

peripapillary RNFL map. The ONH scan consists of 12 radial 148

lines of 3.7 mm length, 2.5–4 mm in diameter, which are used 149

to calculate the disc margin and ONH parameters. Retinal 150

pigment epithelium (RPE)/Bruch’s membrane end tips are 151

automatically detected on the radial image as the disc margin 152

and disc area is calculated. Only good quality images, as 153

defined by the scans with a SSI > 50, without segmentation 154

or algorithm failure or artifacts were included. 155

The enface RPC angiogram images and the enface ONH 156

angiogram image were transferred to a computer to quantify 157

RPC CD and inside the ONH CD. The peripapillary and ONH 158

region were equally divided into 8 equal sectors, which were 159

designated as Superior nasal (SN), Superior temporal (ST), 160

Temporal upper (TU), Temporal lower (TL), Nasal upper 161

(NU), Nasal lower (NL), Inferior nasal (IN) and Inferior tempo- 162

ral (IT) (Fig. 1A and B). MATLAB (Mathworks version R 2014 a) 163

2 T. Mansoori et al.

SJOPT 609 No. of Pages 8, Model NS

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164 software was used for the calculation of CD by a single

165 trained examiner who was masked to the clinical findings.

166 For the RPCs CD analysis, the outer circle was chosen to

167 be at 3.45 mm circle diameter around ONH for all the

168 images, while inner circle is chosen as per the disc size for

169 each eye and for the ONH CD analysis, a set of user-

170 defined points on the ONH boundary was chosen and the

171 best fit circle to these points was marked (Fig. 1B). Capillaries

172 were detected using B-COSFIRE method for the automatic

173 segmentation of blood vessels.¹³The method uses a differ-

174 ence of Gaussians (Do G) filter for vessel detection and the

175 choice of parameters of the Gaussian determines the thick-

176 ness of extracted vessels. These parameters were tuned to

177 extract and suppress the large vessels. The Do G response

178 is thresholded with a value 30 to obtain a binary mask where

179 all the thick vessels are set to 0 and the others are set to 1.

180 Multiplying this mask with the RPCs and ONH Angio flow

181 image yields the desired capillary image (I_C) with only the

182 capillary network. The CD was calculated as: CDðiÞ ¼^N_AðiÞ^w^ðiÞ

183 where i = 1, 2. . . 8, is the sector index, Nw (i) denotes the

184 number of white pixels and A(i) denotes the area of the ith

185 sector of I_C.

186 Statistical analysis

187 Prior to comparison between the groups, numerical data

188 was tested for assumption of homogeneity of variances using

189 the Levene’s test. Descriptive analysis were calculated as the

190 mean and standard deviation. Unpaired t test was used to

191 compare clinical parameters, CD and RNFLT parameters

192 between the sectors in normal subjects and POAG eyes. Cat-

193 egorical variables were compared using the chi square test.

194 Correlation of mean ONH CD with disc area was measured

195 using Pearsons correlation coefficient. Area under the recei-

196 ver operating characteristic (AUROC) curves were used to

197 describe the diagnostic accuracy of RPC and ONH CD for dif-

198 ferentiating between the healthy and POAG eyes. Statistical

199 analysis was performed using commercial SPSS software (ver-

200 sion 19, IBM, Chicago, USA). A P value < 0.05 was considered

201 statistically significant.

Results 202

Seventy four eyes of 74 healthy subjects (mean age, 203

53.1 ± 14.1 years) and 83 eyes of POAG patients (mean 204

age, 53.9 ± 10.7 years) were included in the study. In POAG 205

group, 27 eyes had mild stage, 12 moderate stage and 37 206

had severe stage glaucoma, according to Hodapp-Parrish- 207

Anderson grading scale of severity of visual field defect.¹⁶ 208

Of the 83 POAG eyes, 49 eyes were on prostaglandin ana- 209

logues, 20 on combination of topical carbonic anhydrase inhi- 210

bitor and beta blocker, and 14 on the alpha agonist. Self- 211

reported history of hypertension and diabetes mellitus was 212

more frequent in glaucoma patients when compared with 213

the healthy controls but the difference was not significant 214

(Table 1). 215

Statistically significant differences were found between 216

glaucoma patients and healthy subjects for all ocular param- 217

eters except for IOP [POAG patients had IOP control with 218

Anti-glaucoma medication (AGM)], CCT and the disc area. 219

SSI of the OCT-A and ONH scan was significantly better in 220

the normal eyes when compared to the POAG patients 221

(Table 1). 222

Qualitative assessment of the RPC and ONH CD 223

Healthy subjects had a dense peripapillary RPC network 224

around the ONH and a dense microvascular capillary network 225

inside the ONH, when compared to the eyes with POAG 226

(Fig. 2A–C). There was focal capillary dropout of the RPC 227

and ONH microvascualr network in early (Fig. 2D and E) 228

and moderate stage (Fig. 2F and G) glaucoma. In advanced 229

stage of glaucoma the capillary network became sparser 230

and more attenuated in the peripapillary and ONH region 231

with diffuse capillary loss (Fig. 2H and I). 232

Quantitative assessment of the RPC and ONH CD 233

The mean (±Standard deviation) RPC density was signifi- 234

cantly lower in the POAG eyes (0.12 ± 0.03) when compared 235

to the normal eyes (0.17 ± 0.05) (p < 0.0001). The mean 236

Fig. 1. A. Enface optical coherence tomography angiography image of the left eye of a normal subject: Radial peripapillary capillaries (RPC) and sectors where the RPC capillary density was calculated: Superior nasal (SN), Superior temporal (ST), Temporal upper (TU), Temporal lower (TL), Nasal upper (NU), Nasal lower (NL), Inferior nasal (IN) and Inferior temporal (IT). B. Enface optical coherence tomography angiography image of the optic nerve head (ONH) of the left eye in a normal subject and the sectors where the capillary density was calculated. Disc margin is marked by red elliptical outline.

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237 inside ONH CD was significantly lower in POAG eyes

238 (0.09 ± 0.03) when compared to the normal eyes

239 (0.11 ± 0.02) (p = 0.01) (Table 1).

240 There was no significant correlation between the disc area

241 and mean ONH CD measurements in the healthy eyes (Pear-

242 son correlation coefficient =0.18, p = 0.115) and POAG

243 eyes (Pearson correlation coefficient =0.15, p = 0.154)

244 respectively.

245 Sector- wise analysis revealed that there was a significant

246 difference between RPC CD and ONH CD measurements

247 between the 2 groups, except for the CD of the superior tem-

248 poral sector of the ONH (p = 0.09) (Table 2).

249 The AUROC ± Standard error (SE) for discriminating

250 between the healthy and glaucomatous eyes was

251 0.784 ± 0.038 for mean RPC CD and 0.743 + 0.052 for the

252 mean ONH CD (Table 3). The AUROC for the best parameter

253 for RPC was CD in the IT sector (0.782 ± 0.038) and mean CD

254 (0.784 ± 0.038). The AUROC for the best parameter for

255 inside ONH CD was 0.724 ± 0.051 for the SN sector CD

256 and mean ONH (0.743 ± 0.052).

257 When 0.16 was taken as a cut off value for Mean RPC CD,

258 the sensitivity was 88% and the specificity was 66.2% and for

259 a cutoff value of 0.136 for the mean ONH CD, the sensitivity

260 was 87.8% and the specificity was 58% for glaucoma

261 detection.

262 Discussion

263 In the present study, using OCT-A, the diagnostic accu-

264 racy of the two scanning areas i.e., RPC and ONH CD mea-

265 surements were evaluated for differentiating POAG eyes

266 from the normal eyes. OCT-A measured RPC CD and ONH

267 CD showed focal or diffuse loss of CD based on the glau-

268 coma severity.

269 In 12 normal and 12 glaucomatous eyes (Mean MD:

270 6.05 ± 7.07 dB), Liu et al.⁸ reported AUROC of 0.94 and

271 specificity of 91.7% and sensitivity of 83.3% for peripapillary

272 vessel density measures in a thicker slab from ILM to RPE.

273 Another study evaluated the microvascular bed in the RNFL

274 layer, (which largely reflects the RPCs), and found that the

275 OCT-A circumpapillary vessel density measurement had

276 AUROC of 0.83 for glaucoma detection in 23 healthy and

104 glaucoma subjects (Median MD:3.9 dB).⁵Rao et al.⁹ 277

reported that the AUROCs of the average peripapillary ves- 278

sel density was 0.83 for differentiating between the normal 279

(78 eyes) and POAG patients (64 eyes, Median MD: 280

5.3 dB). Mammo et al.⁷ used a manual tracing technique 281

to quantify RPCs density in the images of Speckle variance 282

OCT-A and reported that the density of RPCs was signifi- 283

cantly lower in glaucomatous eyes (n = 10) when compared 284

with matched – peripapillary regions in normal eyes 285

(n = 16). Wang et al.¹⁰ reported an AUROC of 0.8 for the 286

ONH vessel density, in 20 normal and 62 POAG patients. 287

We found that the AUROC of ONH CD was highest for the 288

SN sector (0.724) and least for the ST sector (0.609). In our 289

study, AUROC for peripapillary sectors ranged between 290

0.782 for IT sector to 0.71 for TL sector. The mean inside 291

ONH CD AUROC was 0.74 and mean peripapillary RPC 292

region CD was 0.78. 293

Previous studies have reported that the ONH vessel den- 294

sity reduction varies between 10% and 34% in glaucomatous 295

eyes when compared to the normal eyes.^6,9–11In the present 296

study, 19% reduction was found in the mean inside disc CD 297

and 18% reduction in the temporal sector in the POAG eyes 298

when compared with the normal eyes. Jia et al.⁶(24 normal 299

subjects and 11 glaucoma patients, Mean MD =3.28) 300

reported that the reduction in ONH vessel density was 301

greater in the temporal part of the ONH (57%), which is 302

devoid of the major retinal vessels, when compared with 303

the entire ONH (34%). Rao et al.⁹reported that the median 304

ONH vessel density decrease was 15% inside ONH when 305

compared with the normal eyes and the vessel density 306

decrease in the temporal sector was 19%. Another study 307

reported that the total ONH vessel density was reduced by 308

25% in glaucoma group (50 eyes) compared to the normal 309

controls (30 eyes) and temporal vessel density was reduced 310

by 23% in glaucoma group (mean MD =10.5).¹¹This differ- 311

ence between the studies may be related to the definition of 312

the ONH sectors area analyzed, definition of temporal sector, 313

methodology used to calculate CD, suppression of large ves- 314

sels during CD analysis and severity of glaucoma disease in 315

the study population. 316

The inside ONH CD in our study showed a large variability 317

when evaluated sector-wise, ranging from 11% reduction in 318

ST sector to 30% reduction in SN sector in glaucomatous 319

Table 1. Ocular and clinical parameters of the study population.

Variables Normal Glaucoma P value

Age (years) 53.13 ± 14.11 53.87 ± 10.73 0.71

Female/male 26/57 34/40 0.06

Self reported history of Diabetes mellitus 6 36 0.05

Self reported history of hypertension 14 30 0.05

Intraocular pressure (mm Hg) 14.27 ± 2.34 14.98 ± 3.13 0.11

Central corneal thickness (microns) 512.2 ± 27.9 513 ± 32.75 0.87

Mean deviation (Decibels) 1.50 ± 0.74 12.04 ± 8.51 <0.0001

Pattern standard deviation (Decibels) 1.67 ± 0.43 6.74 ± 5.16 <0.0001

Signal strength index (OCT-A) 71.73 ± 11.31 62.49 ± 9.02 <0.0001

Mean peripapillary capillary density 0.17 ± 0.05 0.12 ± 0.03 <0.0001

Mean inside Optic nerve head capillary density 0.11 ± 0.02 0.09 ± 0.03 0.01

Signal strength index (Optic nerve head) 70.38 ± 12.7 59 ± 9.77 <0.0001

Average Retinal nerve fiber layer (microns) 100.57 ± 10.31 75.46 ± 15.71 <0.0001

Cup disc vertical ratio 0.58 ± 0.14 0.85 ± 0.11 <0.0001

Cup disc horizontal ratio 0.67 ± 0.15 0.89 ± 0.11 <0.0001

Rim area (mm²) 1.25 ± 0.26 0.65 ± 0.26 <0.0001

Disc area (mm²) 2.23 ± 0.43 2.24 ± 0.5 0.89

OCT-A: Optical coherence tomography angiography.

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Fig. 2. A. Normal eyes – Dense radial peripapillary capillaries network and optic nerve head microvascular network in the enface image of optical coherence tomography angiography B. Suppression of the large vessels for the analysis. C. Capillary density image of the normal eye after suppression of the large vessels. D. Mild glaucoma – Enface optical coherence tomography angiography image shows slit shaped focal loss of radial peripapillary capillaries (arrow). E. Enface optical coherence tomography angiography of the Optic nerve head with mild attenuation of the capillaries inferiorly on the optic nerve head in a patient with mild glaucoma. F. Moderate glaucoma – Enface optical coherence tomography angiography image shows a Wedge shaped wide capillary loss in the infero-nasal and infero-temporal sectors and supero-temporal and temporal upper sector (arrow). G. Enface optical coherence tomography angiography image with attenuation of capillaries (arrow) on the Optic nerve head in an eye with moderate glaucoma. H. Severe glaucoma – Enface optical coherence tomography angiography image depicting a diffuse radial peripapillary capillary loss and in microvascular network in the Optic nerve head with diffuse loss of capillary density in the temporal sector I. Enface optical coherence tomography angiography image with diffuse loss of the capillaries on the Optic nerve head, in an eye with severe glaucoma.

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Fig. 2 (continued)

Table 2. Sector wise analysis of peripapillary capillary density, inside optic nerve head capillary density and retinal nerve fiber layer thickness in the glaucoma patients.

Sectorwise peripapillary CD Glaucoma Normal P value

Mean SD Mean SD

Temporal upper 0.1085 0.0417 0.1655 0.0650 <0.0001

Superior temporal 0.1562 0.0446 0.2057 0.0601 <0.0001

Superior nasal 0.0940 0.0310 0.1454 0.0555 <0.0001

Nasal upper 0.1133 0.0405 0.1687 0.0636 <0.0001

Nasal lower 0.1303 0.0456 0.1812 0.0595 <0.0001

Inferior nasal 0.0950 0.0346 0.1431 0.0604 <0.0001

Inferior temporal 0.1620 0.0499 0.2076 0.0636 <0.0001

Temporal lower 0.1103 0.0365 0.1794 0.0723 <0.0001

Sectorwise inside optic nerve head CD

Temporal upper 0.1641 0.0661 0.1892 0.0507 0.04

Superior temporal 0.1352 0.0557 0.1527 0.0455 0.095

Superior nasal 0.0973 0.0475 0.1399 0.0515 <0.0001

Nasal upper 0.1232 0.0519 0.1494 0.0457 0.01

Nasal lower 0.1336 0.0548 0.1570 0.0534 0.04

Inferior nasal 0.1083 0.0494 0.1256 0.0445 <0.0001

Inferior temporal 0.1338 0.0511 0.1543 0.0478 0.045

Temporal lower 0.1655 0.0606 0.2127 0.0503 <0.0001

CD: Capillary density.

SD: Standard deviation.

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320 eyes when compared with the normal subjects. The variability

321 was less when analyzed quadrant-wise, i.e., 13% CD reduc-

322 tion for the inferior quadrant to 20% CD reduction for supe-

323 rior quadrant in the glaucomatous eyes.

324 Previous OCT-A studies have reported 11–13% reduction

325 of peripapillary vessel density in glaucoma patients when

326 compared to normal controls.^8,9 Liu et al.⁸ assessed both

327 the superficial and deep capillary beds and calculated the

328 vascular parameters in a thicker retinal slab from the ILM to

329 the RPE. We found 29% reduction in the mean RPC peripap-

330 illary CD in glaucomatous eyes when compared to the normal

331 eyes. This difference among the studies could be because of

332 the fact that the severity of glaucoma in our study patients

333 (Mean MD:12.D) was more than that in the other reported

334 studies.^8,9 Also, we used B-COSFIRE method for the auto-

335 matic segmentation of blood vessels and suppressed the

336 large vessels during CD analysis and the methodology used

337 to calculate ONH CD and RPC was different.

338 The difference in the two scanning region for the CD mea-

339 surement i.e. peripapillary RPC and ONH region could be

340 due to the physiological variations in the disc size and shape,

341 disc tilt, area of peripapillary atrophy (PPA), position of exit of

342 the major trunk of central retinal vessels on the ONH surface.

343 However, we did not find a significant correlation between

344 the disc size and ONH CD measurements in normal and

345 POAG eyes. Also, we did not measure the area of PPA in

346 our study, though none of the patients had significant PPA.

347 The limitations of the current study is that we did not eval-

348 uate the possible confounding effect of Diabetes mellitus,

349 systemic hypertension, ocular perfusion pressure, ocular anti-

350 hypertensive medications and AGM on the CD measure-

351 ment. Therefore, we could not rule out the impact of

352 systemic diseases, medications and AGM on the CD

353 measurements.

354 Conclusion

355 The present study demonstrated that OCT-A derived RPC

356 density and inside ONH CD is significantly reduced in the

POAG eyes when compared with the healthy control eyes. 357

These parameters have a moderate diagnostic accuracy for 358

discriminating healthy eyes from glaucoma patients. Diag- 359

nostic ability of even the best parameter, i.e., mean and IT 360

sector peripapillary sector RPC CD and SN sector and mean 361

ONH CD parameter was only moderate. Further studies are 362

needed to determine the usefulness of the peripapillary 363

RPC CD and ONH CD loss, found in the POAG patients in 364

the glaucoma diagnosis. 365

Conflict of interest 366

The authors declared that there is no conflict of interest. 367

Financial interest 368

None. 369

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Table 3. Area under receiver operator curve (AUROC) for the inside optic nerve head (ONH) capillary density (CD) and peripapillary CD to differentiate between the normal and glaucomatous eye using optical coherence tomography angiography.

Variables AUROC Standard error 95% confidence interval

Lower bound

95% confidence interval Upper bound

P value

Sector-wise optic nerve head capillary density (CD)

Superior temporal 0.609 0.058 0.495 0.723 0.065

Temporal upper 0.617 0.058 0.504 0.730 0.048

Superior nasal 0.724 0.051 0.624 0.825 <0.0001

Nasal upper 0.663 0.055 0.555 0.771 0.006

Temporal lower 0.713 0.053 0.609 0.816 <0.0001

Inferior temporal 0.638 0.057 0.526 0.749 0.020

Nasal lower 0.673 0.055 0.564 0.781 0.004

Inferior nasal 0.633 0.058 0.519 0.748 0.024

Mean ONH CD 0.743 0.052 0.642 0.844 <0.0001

Sector-wise peripapillary capillary density (CD)

Temporal upper 0.747 0.040 0.668 0.826 <0.0001

Superior temporal 0.761 0.040 0.682 0.840 <0.0001

Superior nasal 0.774 0.038 0.699 0.850 <0.0001

Nasal upper 0.760 0.039 0.683 0.837 <0.0001

Nasal lower 0.751 0.039 0.675 0.827 <0.0001

Inferior nasal 0.745 0.040 0.666 0.824 <0.0001

Inferior temporal 0.782 0.038 0.708 0.857 <0.0001

Temporal lower 0.710 0.042 0.626 0.793 <0.0001

Mean peripapillary CD 0.784 0.038 0.709 0.859 <0.0001

(8)

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